Concept and benchmark results for Big Data energy forecasting based on Apache Spark

Abstract

Abstract The present article describes a concept for the creation and application of energy forecasting models in a distributed environment. Additionally, a benchmark comparing the time required for the training and application of data-driven forecasting models on a single computer and a computing cluster is presented. This comparison is based on a simulated dataset and both R and Apache Spark are used. Furthermore, the obtained results show certain points in which the utilization of distributed computing based on Spark may be advantageous.

Keywords

• Big Data
• Forecasting
• Energy
• Data-driven
• EnergyLab 2.0